title: Budget impact model of rituximab after failure of one or more TNFalpha inhibitor therapies in the treatment of rheumatoid arthritis.
abstract: OBJECTIVE
  To estimate the budget impact implied by the introduction of rituximab after failure of one or more anti-TNFalpha therapies in the perspective of the French health care system.
  
  
  METHODS
  A Markov model reproduced the course, over 4years, of patients treated either by infliximab, etanercept, adalimumab or RTX, after failure of one or more anti-TNFalpha therapies, in a multicentric study. A sensitivity analysis was developed to account for patients in 3rd and subsequent lines of treatment who are expected to consume more healthcare resources.
  
  
  RESULTS
  When RTX is not used, total annual medical cost is euro16,555 per patient, euro13,206 of which are dedicated to drug acquisition. When RTX is the only treatment in use, these costs decrease respectively to euro11,444 and euro7469. Total savings per patient and per year is euro5000. Over 4 years, total savings for the targeted population reach euro118M. In the sensitivity analysis, the difference between H2 and H2-coeff 2 (20%) reaches euro5,400,000 in total direct costs during the first year of simulation. This difference decreases along the period, to reach euro2,400,000 the fourth year of simulation, and is due to the fact that rituximab acquisition costs are independent from the treatment line.
  
  
  CONCLUSIONS
  If TNFalpha inhibitors were the only treatment available, the annual global cost of treatment would be euro16,555 per patient versus euro11,444 for patients treated exclusively with rituximab. RTX is expected to produce important savings (-31%) if used after failure of one or more TNFalpha therapies. This is mainly due to its lower drug acquisition cost. These savings could increase with the development of rituximab in earlier stages of treatment.
authors.affiliation: REES France, Paris, France. launois.reesfrance@wanadoo.fr
authors.forename: Robert
authors.initials: R
authors.lastname: Launois
authors.forename: Stéphanie
authors.initials: S
authors.lastname: Payet
authors.forename: Nathalie
authors.initials: N
authors.lastname: Saidenberg-Kermanac'h
authors.forename: Camille
authors.initials: C
authors.lastname: Francesconi
authors.forename: Lionel Riou
authors.initials: LR
authors.lastname: França
authors.forename: Marie-Christophe
authors.initials: MC
authors.lastname: Boissier
mesh_terms: D000911:Antibodies, Monoclonal / Q000191:economics* / Q000627:therapeutic use; D058846:Antibodies, Monoclonal, Murine-Derived; D018501:Antirheumatic Agents / Q000191:economics* / Q000627:therapeutic use; D001172:Arthritis, Rheumatoid / Q000188:drug therapy / Q000191:economics*; D004363:Drug Utilization / Q000706:statistics & numerical data; D017048:Health Care Costs; D006801:Humans; D008390:Markov Chains; D012219:Rheumatology / Q000191:economics*; D000069283:Rituximab; D012680:Sensitivity and Specificity
chemical_list: D000911:Antibodies, Monoclonal; D058846:Antibodies, Monoclonal, Murine-Derived; D018501:Antirheumatic Agents; D000069283:Rituximab